The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...

Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimiz...

Based on classical plate theory, standard and spectral finite element methods are extended for vibration and dynamic stability of axially moving thin plates subjected to in-plane forces. The formulation of the standard method earned through Hamilton’s principle is independent of element type. But for solving numerical examples, an isoparametric quadrilateral element is developed using Lagrange ...

Based on classical plate theory, standard and spectral finite element methods are extended for vibration and dynamic stability of axially moving thin plates subjected to in-plane forces. The formulation of the standard method earned through Hamilton’s principle is independent of element type. But for solving numerical examples, an isoparametric quadrilateral element is developed using Lagrange ...

These days randomized-based population optimization algorithms are in wide use in different branches of science such as bioinformatics, chemical physics andpower engineering. An important group of these algorithms is inspired by physical processes or entities’ behavior. A new approach of applying optimization-based social relationships among the members of a community is investigated in this pa...

Seas and oceans are the most important sources of renewable energy in the world. The main purpose of this paper is to use an appropriate control strategy to improve the performance of point absorbers. In this scheme, considering the high uncertainty in the parameters of the power take-off system in different atmospheric conditions, a new improved black hole algorithm is introduced to tune fuzzy...

Digital signal processing (DSP) industry has been growing rapidly over the past few years; it remains the technology driver for the recovering semiconductor industry. Performance evaluation is essential for the users and manufacturers of DSP processors. Since DSP application programs become larger and more complicated, people need new benchmarks for performance evaluation of different DSP proce...

The choice of which objective functions, or benchmark problems, should be used to test an optimization algorithm is a crucial part the selection framework. Benchmark suites that are often in literature have been shown exhibit poor coverage problem space. Exploratory landscape analysis can quantify characteristics functions. However, exploratory measures based on samples function, and there lack...

We design and analyze minimax-optimal algorithms for online linear optimization games where the player’s choice is unconstrained. The player strives to minimize regret, the difference between his loss and the loss of a post-hoc benchmark strategy. While the standard benchmark is the loss of the best strategy chosen from a bounded comparator set, we consider a very broad range of benchmark funct...